An efficient near-duplicate video shot detection method using shot-based interest points

  • Authors:

  • Xiangmin Zhou;Xiaofang Zhou;Lei Chen;Athman Bouguettaya;Nong Xiao;John A. Taylor

  • Affiliations:

  • CSIRO, ICT Center, Canberra, Australia;School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia;Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China;CSIRO, ICT Center, Canberra, Australia;National University of Defense Technology, Changsha, China;CSIRO, ICT Center, Canberra, Australia

  • Venue:
  • IEEE Transactions on Multimedia
  • Year:
  • 2009

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Abstract

We propose a shot-based interest point selection approach for effective and efficient near-duplicate search over a large collection of video shots. The basic idea is to eliminate the local descriptors with lower frequencies among the selected video frames from a shot to ensure that the shot representation is compact and discriminative. Specifically, we propose an adaptive frame selection strategy called furthest point voronoi (FPV) to produce the shot frame set according to the shot content and frame distribution. We describe a novel strategy named reference extraction (RE) to extract the shot interest descriptors from a keyframe with the support of the selected frame set. We demonstrate the effectiveness and efficiency of the proposed approaches with extensive experiments.